Optimizing geometric parameters of Archimedean water turbine

被引:0
|
作者
Shahverdi, Kazem [1 ]
机构
[1] Bu Ali Sina Univ, Fac Agr, Dept Water Sci & Engn, Hamadan, Iran
关键词
Grew wolves optimization; Particle swarm optimization; Renewable energy; PARTICLE SWARM; SCREW TURBINE; OPTIMIZATION; MODEL;
D O I
10.1016/j.ref.2024.100601
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Archimedean turbines have recently been installed in watercourses to convert the hydraulic power of water to electricity. As a new technology, they are under development now. Its geometric parameters' optimization with heuristic optimizers hasn't been considered so far. These parameters include the ratio of the inner to the outer diameter (diameter ratio), the pitch to the outer diameter ratio (pitch ratio), the tilt angle, and the fill factor which is the ratio of water depth in the screw's bucket to the outer diameter. In this research, the efficiency prediction model of the Archimedean turbine was coded in MATLAB and validated with laboratory and field Archimedean turbine data. Then, particle swarm optimizer (PSO) and grey wolves optimizer (GWO) were developed and linked with the validated prediction model. The optimizers' convergence was investigated; then, the turbine parameters were optimized to obtain the maximum efficiency. The best value of the tilt angle was found in the range 20-22.5 degrees, and the best value of the fill factor was 1. The maximum mechanical efficiency of about 90% was found in this research. The overall results of PSO were better than GWO.
引用
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页数:7
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